This book gathers the proceedings of the 15th International Conference on Frontier Computing, held in Osaka, on July 610, 2025, and provides comprehensive coverage of the latest advances and trends in information technology, science, and engineering. It addresses a number of broad themes, including communication networks, business intelligence and knowledge management, Web intelligence, and related fields that inspire the development of information technology. The respective contributions cover a wide range of topics: database and data mining, networking and communications, Web and Internet of things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. Many of the papers outline promising future research directions, and the book benefits students, researchers, and professionals alike. Further, it offers a useful reference guide for newcomers to the field.

Demonstrates the progress of the most advanced information technologies Describes the novel ideas and applications of frontier computing Covers mainstream issues of computer science, application on cloud computing, information security, big data

Autorentext

Dr. Jason C. Hung is a Professor of Department of Computer Science and Information Engineering at National Taichung University of Science and Technology, Taiwan, ROC. His research interests include Multimedia Computing and Networking, e- Learning, Web Service and Anticipatory Computing. Dr. Hung received his BS and MS degrees in Computer Science and Information Engineering from Tamkang University, in 1996 and 1998, respectively. He also received his Ph.D. in Computer Science and Information Engineering from Tamkang University in 2001. He is the founder of International Conference on Frontier Computing. In 2013, He served as Hon Treasurer of IET Taipei LN. In April of 2014, he was elected as Fellow of the Institution of Engineering and Technology (FIET). He was elected as vice chair of IET Taipei LN in Nov. 2014. From June 2015, He is Editor-in-Chief of International Journal of Cognitive Performance Support.

Dr. Neil Y. Yen is an Associate Professor at the University of Aizu, Japan. Dr. Yen received doctorates in Human Sciences (major in Human Informatics) at Waseda University, Japan, and in Engineering (major in Computer Science) at Tamkang University, Taiwan in March and June 2012 respectively. His doctor degree at Waseda University was funded by the JSPS (Japan Society for the Promotion of Science) under RONPAKU program. Dr. Yen has actively involved himself in the international activities, including editorial works in journals and books, society services in academic conferences sponsored by IEEE/ACM, etc., and devoted himself to discover advanced and interesting research directions. Dr. Yen has been engaged in the interdisciplinary realms of research, and his research interests are now primarily in the scope of human-centered computing and big data.

Dr. Jia-Wei Chang is an Associate Professor in Department of Computer Science and Information Engineering at National Taichung University of Science and Technology. Since January 2019, he is a Young Professionals Chair of the Institution of Engineering and Technology (IET) - Taipei Network. Since 2017, he is a consultant of NEXCOM Industry 4.0 Innovation Center. During February to July 2018, he was an adjunct assistant professor in Department of Engineering Science at National Cheng Kung University. He was a data scientist and project manager at IoT BU, Nexcom during 2016-2017. He received the Ph.D. degree from Department of Engineering Science, National Cheng Kung University in 2017. His research interests include natural language processing, internet of things, artificial intelligence, data mining, and e-learning technologies.

Inhalt

Prediction Model of Chronic Disease Management for the Elderly Based On Sensor Data -. **** Research on Color Recognition Intelligent Handling Robot Based on the SLAM.- Impact of Pre-trained Language Models on Translation Quality.- Adversarial Sample Defense Mechanism for Network Intrusion Detection System Based on Generative Adversarial Network.- Personalized Layout Design of Indoor Space Based on Generative Adversarial Network Algorithm.- Construction of Digital Autonomous Learning Platform Based on Bayesian Network.- Automatic Recognition and Layout of Image Content Based on DenseNet Model.- Efficient Transmission and Intelligent Processing Technology of Distribution Network Fault Data Integrated with GPT.- A Spatialization Method of Film and Television Audio based on Deep Learning.- Cross-Layer Collaborative Optimization Method in Next Generation Communication Networks .